Government digital transformation, resource curse and green total factor energy efficiency in Chinese cities

Fan Bie, Luyao Zhou, Shuo Liu and Tao Yang

Resources Policy, 2024, vol. 92, issue C

Abstract: In the age of digitalization, Government Digital Transformation (GDD) stands out as a critical gauge of a nation's modernization drive. It reflects the extent of modernization within the governance framework and acts as a central catalyst for improving governance efficiency and the overall modernity of the system. Against this backdrop, this study empirically investigates the impact of GDD on green total factor energy efficiency (GTFEE) from 2011 to 2020, focusing on prefecture-level cities in China. Using a two-way fixed-effects model, we analyze how GDD influences GTFEE. Additionally, we explore the mediating effect and threshold models to elucidate the mechanisms underlying the resource curse (RC). The findings of the study are as follows: first, GDD has a promoting effect on GTFEE; second, the promoting effect of GDD on GTFEE is more obvious in southern cities and fourth-tier cities; third, the RC plays a mediating effect in the relationship between GDD and GTFEE, specifically, GDD promotes GTFEE by suppressing the RC effect and then promotes GTFEE; fourth, the present study also identifies a RC threshold effect; when RC < 0.5127, the energy efficiency promotion effect of GDD is relatively limited, while when RC ≥ 0.5127, the promotion effect of GDD on GTFEE is significantly enhanced. These findings are of great value for understanding and optimizing the strategic significance of GDD in enhancing GTFEE. They provide a scientific basis and directional guidance for formulating and implementing related policies.

Keywords: Government digital transformation; Resource curse; Green energy efficiency; Fixed effects model; Mediation effects model; Threshold model (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:92:y:2024:i:c:s0301420724003696

DOI: 10.1016/j.resourpol.2024.105002

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